IMR Press / JIN / Volume 21 / Issue 2 / DOI: 10.31083/j.jin2102055
Open Access Original Research
Identification of a novel immune-related lncRNA signature to predict prognostic outcome and therapeutic efficacy of LGG
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1 Department of Neurosurgery, The First Medical Centre, Chinese PLA General Hospital, 100853 Beijing, China
2 Department of General Surgery, The Air Force Hospital of Northern Theater PLA, 110042 Shenyang, Liaoning, China
3 Department of General Surgery, Chinese PLA General Hospital, 100853 Beijing, China
4 Department of Neurosurgery, The Second Hospital of Southern Theater of Chinese Navy, 572000 Sanya, Hainan, China
*Correspondence: (Meng Zhang)
These authors contributed equally.
Academic Editor: Gary Dunbar
J. Integr. Neurosci. 2022, 21(2), 55;
Submitted: 1 December 2021 | Revised: 11 January 2022 | Accepted: 13 January 2022 | Published: 22 March 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.

Background: Recent studies have shown that the prognosis of low-grade glioma (LGG) patients is closely correlated with the immune infiltration and the expression of long-stranded non-coding RNAs (lncRNAs). It’s meaningful to find the immune-related lncRNAs (irlncRNAs). Methods: The Cancer Genome Atlas (TCGA) data was employed in the study to identify irlncRNAs and Cox regression model was applied to construct the risk proportional model based on irlncRNAs. Results: In the study, we retrieved transcriptomic data of LGG from TCGA and identified 10 lncRNA signatures consisting of irlncRNAs by co-expression analysis. Then we plotted 1-year receiver operating characteristic (ROC) curves and calculated the area under the curve (AUC). LGG patients were divided into high-risk and low-risk groups according to the risk model. We found there were differences in survival prognosis, clinical characteristics, degree of immune cell infiltration, expression of immune gene checkpoint genes, and sensitivity to the commonly used chemotherapeutic agents of high-risk and low-risk groups. Conclusions: IrlncRNA-based risk assessment model can be used as a prognostic tool to predict the survival outcome and clinical characteristics of LGG and to guide treatment options.

Low-grade gliomas
Immune cell infiltration
Chemotherapy sensitivity
Fig. 1.
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